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Image compression plays more and more important role in image processing. Image sparse coding with learned over-complete dictionaries shows promising results on image compression by representing images with dictionary atoms compactly. Within the sparse coding based compression framework, a sparse dictionary is first learned from training images in a predefined image library, and then an image is compressed...
Nowadays, more and more methods have been proposed to solve the problem of face detection based on computer implementation. Due to the variations in background, illumination, pose and facial expressions, the problem of machine face detection is complex. Recently, deep learning approaches achieve an impressive performance on face detection. In this paper, a model named Multi-Scale Fusion Convolutional...
A robotic fish should be designed to swim with the obstacle avoidance capability in the real world. In this paper, a neuro-fuzzy control method is proposed for a multi-joint robotic fish using 3D printing technology. For this method, we can use the general infrared sensors to measure the existence of obstacles and the distance from the robotic fish to the obstacles. With the inference and learning...
Text-based sentiment analysis is a growing research field in affective computing, driven by both commercial applications and academic interest. Continuous dimensional representations, such as valence-arousal (VA) space, can represent the affective state more precisely than discrete effective representations. In building dimensional sentiment applications, affective lexicons with valence-arousal ratings...
Short text is a popular text form, which is widely used in short commentary, micro-blog and many other fields. With the development of the social software and movie websites, the size of data is also becoming larger and larger. Most data is useless for us while other data is important for us. Therefore, it is very necessary for us to extract the useful short text from the big data. However, there...
With the continuous development of the information technology, ontology has been widely applied to various fields. Ontology has become an advanced technology in artificial intelligence and knowledge engineering, playing an increasingly important role in knowledge representation, knowledge acquisition and ontology application. As the base of ontology applications, ontology construction and ontology...
Data-driven soft sensors have been widely used in both academic research and industrial applications for predicting hard-to-measure variables or replacing physical sensors to reduce cost. It has been shown that the performance of these data-driven soft sensors can be greatly improved by selecting only the vital variables that strongly affect the primary variables, rather than using all the available...
Hyper networks consist of a large number of hyper edges that represent high-order features sampled from training sets. The order of hyper edges is an important parameter of a hyper network model and influences the performance of the hyper network classification system. Previous studies determine the parameter by the artificial exhaustive search method before evolutionary learning. Not only is the...
Sensitive information, e.g. sex-related, violate news, hinders a lot to content advertising, especially for mobile environment. This paper presents a sensitivity-proof content advertising method by utilizing two-stage text classification. The two stages are advertisement (Ad) classification and sensitivity detection in sequence. A policy is established to combine the results of the two stages for...
To track the state of charge (SOC) of Ni-MH battery pack at the hybrid electric vehicle, an artificial neural network (ANN) is designed. Current, voltage and the previous SOC are used to inputs of ANN, and output is SOC. The result show that, this artificial neural network can track the state of charge (SOC) of the batteries accurately, in the average tracking error less than 5%; the ANN is in low...
Motivated by the application of the 2D principal component analysis (PCA) for face recognition, this study proposes a modified multilinear PCA method as means to provide higher accuracy with comparable processing time in contrast to the results of contemporary methods. This comparative study includes an assessment of the accuracy and processing time of the independent component analysis (ICA), the...
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